title: Artificial neural networks (ANN) approach for modeling of removal of Lanaset Red G on Chara contraria.
abstract: A three-layer artificial neural network (ANN) was constructed to predict the removal efficiency of Lanaset Red (LR) G on Chara contraria based on 2304 experimental sets. The effects of operating variables (particle size, adsorbent dosage, pH regimes, dye concentration, and contact time) were studied to optimize the sorption conditions of this dye. The operating variables were used as the input to the constructed neural network to predict the dye uptake at any time as the output. This adsorbent was characterized by FTIR. Pseudo second-order model was also fitted to the experimental data. According to values of error analyses and determinations coefficient, the ANN was more appropriate to describe this adsorption process. Result of this model indicated that pH regimes had the highest importance effect (49%) on the dye uptake.
authors.affiliation: Department of Biology, Faculty of Art and Science, University of Gaziantep, 27310 Gaziantep, Turkey. celekli.a@gmail.com
authors.forename: Abuzer
authors.initials: A
authors.lastname: Celekli
authors.forename: Faruk
authors.initials: F
authors.lastname: Geyik
mesh_terms: D000327:Adsorption; D044784:Chara / Q000378:metabolism*; D004396:Coloring Agents / Q000302:isolation & purification*; D006863:Hydrogen-Ion Concentration; D007700:Kinetics; D008956:Models, Chemical; D016571:Neural Networks, Computer; D010316:Particle Size
chemical_list: D004396:Coloring Agents